The correct option is Data Ingestion.

Capturing raw telemetry events from drones and writing each event to a Cloud Storage landing bucket for retention before any parsing, filtering, or transformation is the activity of bringing data into the platform and persisting it in its original form so that later stages can use it. This is the intake stage of the machine learning lifecycle where data is collected and stored as is to enable subsequent validation, preparation, and modeling steps.

Model Deployment is about pushing a trained model into a serving environment for online or batch predictions and it does not involve collecting or landing raw events.

Data Preparation covers cleaning, parsing, filtering, transforming, and feature engineering. The scenario states that none of these steps occur yet, which means this phase has not started.

Model Training involves fitting algorithms to prepared data to learn parameters. The described activity does not train any model.

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